• The Journal of Engineering Geology
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• v.23 no.4
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• pp.477-491
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• 2013

Natural radionuclides in groundwater in the Danyang area were investigated to characterize the behaviors of uranium and radon with respect to lithology and physico-chemical components, which can aid our understanding of their occurrence, properties, and origins. To this end, a total of 100 groundwater samples were collected and analyzed, and radionuclide levels were used to construct detailed concentration maps. The water type of the groundwater, assessed using a Piper diagram, is mainly Ca-Na-$HCO_3$. The concentrations of uranium range from 0.02 to $251.0{\mu}g/L$ (average, $3.85{\mu}g/L$) and only 1% exceed USEPA's MCL (Maximum Contaminant Level). Uranium is enriched in groundwaters of Cretaceous granites and Precambrian metamorphic rocks, whereas it is depleted in groundwaters of sedimentary rocks. The concentrations of radon range from 13 to 28,470 pCi/L (average, 2397 pCi/L). Only 15% of the samples exceed AMCL (Alternative Maximum Contaminant Level) of 4000 pCi/L. The radon concentration is highest in groundwater of Cretaceous granites and lowest in groundwater of sedimentary rocks. In conclusion, the distribution and occurrence of radionuclides are intimately related to the basic geological characteristics of the rocks in which the radiogenic minerals are primarily contained. The behavior of uranium is only weakly related to that of radon (correlation coefficient = 0.15). There are also weak correlations between radionuclides and the main chemical components, pH, EC, Eh, and well depth. Of note, the correlation coefficient between radon and $SiO_2$ is 0.68, and that between radon and $HCO_3$ is -0.48. Factor analysis shows that radionuclides behave somewhat independently of each other because there are no significant factors that control the behavior of chemical components as well as radionuclides. The detailed concentration maps during this study will be used to establish useful database of radionuclide distribution and geological properties throughout Korea.

• Radiation Oncology Journal
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• v.29 no.3
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• pp.164-173
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• 2011

Purpose: This research aimed to analyze the patterns of co-authorship network among the Korean radiation oncologists and to identify attributing factors for the formation of networks. Materials and Methods: A total of 1,447 articles including contents of ‘Radiation Oncology' and 'Therapeutic Radiology' were searched from the KoreaMed database. The co-authorship was assorted by the author's full name, affiliation and specialties. UCINET 6.0 was used to fi gure out the author's network centrality and the cluster analysis, and KeyPlayer 1.44 program was used to get a result of key player index. Sociogram was analyzed with the Netdraw 2.090. The statistical comparison was performed by a t-test and ANOVA using SPSS 16.0 with p-value < 0.05 as the significant value. Results: The number of articles written by a radiation oncologist as the first author was 1,025 out of 1,447. The pattern of coauthorship was classified into five groups. For articles of which the first author was a radiation oncologist, the number of singleauthor articles (type-A) was 81; single-institution articles (type-B) was 687; and multiple-author articles (type-C) was 257. For the articles which radiation oncologists participated in as a co-author, the number of single-institution articles (type-D) was 280 while multiple-institution articles (type-E) were 142. There were 8,895 authors from 1,366 co-authored articles, thus the average number of authors per article was 6.51. It was 5.73 for type-B, 6.44 for type-C, 7.90 for type-D, and 7.67 for type-E (p = 0.000) in the average number of authors per article. The number of authors for articles from the hospitals published more than 100 articles was 7.23 while form others was 5.94 (p = 0.005). Its number was 5.94 and 7.16 for the articles published before and after 2001 (p = 0.000). The articles written by a radiation oncologist as the first author had 5.92 authors while others for 7.82 (p = 0.025). Its number was 5.57 and 7.71 for the Journal of the Korean Society for Therapeutic Radiology and Oncology and others (p = 0.000), respectively. Among the analysis, a significant difference in the average number of author per article was indicated. The out-degree centrality of network among authors was 4.26% (2.03-7.09%) while in-degree centrality was 1.31% (0.53-2.84%). The three significant nodes were classified and listed as following: Choi, Eun Kyung for 1991-1995, Kim, Dae Young for 1998-2001, Park, Won and Lee, Sang Wook for 2003-2010. Choi, Eun Kyung and Kim, Dae Young appeared in two cases, and ranked as the highest degree in centrality. In the key player analysis, Choi, Eun Kyung and Lee, Sang Wook appeared in two cases, and ranked as the highest. From the cluster analysis, Sungkyunkwan University, Seoul National University and Yonsei University revealed as the three large clusters when Ulsan University, Chonnam National University, and Korea Institute of Radiological & Medical Science as the medium clusters. Conclusion: The Korean radiation oncologist's society shows a closed network with numerous relationships among the particular clusters, and the result indicates it is different from other institutions in the pattern of co-authorship formation of the major hospitals.

• Korean Journal of Microbiology
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• v.42 no.1
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• pp.40-46
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• 2006

Galactose joined to glucose by a $\beta(1\rightarrow4)$ glycosidic bond makes lactose and this disaccharide is rich in milk. It is known that lacotse is hydrolyzed to each monomeric sugar by either lactase in human or $\beta-galactosidase$ in bacteria. Ingestion of milk by lactase-deficient persons causes a temporary diarrhea and subsequent chronic diarrhea results in colitis with chronic inflammation. We isolated a $\beta-galactosidase$ producing psycrotolerant strain AS-20 from near cattle shed and investigated the growth at various temperature conditions. Whereas Escherichia coli strains did not grow at $10^{\circ}C$, the AS-20 strain could grow well at this low temperature and showed optimal growth at $30^{\circ}C$. The isolated strain was identified as 97% Hafnia alvei by biochemical properties. This strain could ferment glucose, lacotse, maltose, mannitol, xylose, ONPG, rhamanose and L-arabinose, and decarboxylate lysin and ornithine. To confirm the identity of isolated strain we amplified 16S rDNA by PCR and searched similarity of the 1426 bp DNA sequcence with Genbank database. The strain AS-20 showed 99% similarity with Hafnia alvei. The activity of $\beta-galactosidase$ was 1.5 times higher when the cell was grown at 10 or $20^{\circ}C$ than at $30^{\circ}C$. The highest enzyme activity of AS-20 was also much higher than that of E. coli, which was grown at $30^{\circ}C$.

• Management & Information Systems Review
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• v.29 no.2
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• pp.1-25
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• 2010

This study attempted to empirically test the determinants of stock returns in Korean stock market applying multi-factor model proposed by Haugen and Baker(1996). Regression models were developed using 16 variables related to liquidity, risk, historical price, price level, and profitability as independent variables and 690 stock monthly returns as dependent variable. For the statistical analysis, the data were collected from the Kis Value database and the tests of forecasting power in this study minimized various possible bias discussed in the literature as possible. The statistical results indicated that: 1) Liquidity, one-month excess return, three-month excess return, PER, ROE, and volatility of total return affect stock returns simultaneously. 2) Liquidity, one-month excess return, three-month excess return, six-month excess return, PSR, PBR, ROE, and EPS have an antecedent influence on stock returns. Meanwhile, realized returns of decile portfolios increase in proportion to predicted returns. This results supported previous study by Haugen and Baker(1996) and indicated that firm-characteristic model can better predict stock returns than CAPM. 3) The firm-characteristic model has better predictive power than Fama-French three-factor model, which indicates that a portfolio constructed based on this model can achieve excess return. This study found that expected return factor models are accurate, which is consistent with other countries' results. There exists a surprising degree of commonality in the factors that are most important in determining the expected returns among different stocks.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.15 no.2
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• pp.193-208
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• 2020

In this study, we investigate the effects of technology innovation investments and employment on credit ratings of very small start-up businesses using the data period of 2009 till 2015 test two hypotheses: asymmetric information hypothesis or competence hypothesis. We use financial and non-financial data of 51,903 observations of 12,028 small businesses from a database of a commercial bank and fixed effects panel models and two-stage instrumental variable models. We find that in the short-run small size startups show lower credit ratings than non-startups, and that both technology innovation activities and employment capability improve their credit ratings. In the long-run, technology innovation investments do not improve their credit ratings of later years while employment capability improve their credit ratings of the subsequent year. In addition, the age of startups improves their credit ratings of the current year and until the subsequent two years while employee productivity, fixed ratio and ROA positively affect their credit ratings for up to three years. However, short-term and overall debt ratios, cost of borrowings and firm-size negatively affect their credit ratings for up to three years. The results of the study on credit ratings suggest that credit rating agencies seem to consider both technology innovation activities and employment capability in the credit ratings of small start-ups as 'competence factors' rather than 'asymmetric information factors' with inefficiency and cost burdens. The results also suggest that we must find ways to reflect properly the severe asymmetric information of the early-stage start-ups, and technology innovation activities and employment capability in the credit rating formula.

• Journal of forensic and investigative science
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• v.1 no.2
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• pp.5-19
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• 2006

Data mining is an information extraction activity to discover hidden facts contained in databases. Using a combination of machine learning, statistical analysis, modeling techniques and database technology, data mining finds patterns and subtle relationships in data and infers rules that allow the prediction of future results. Typical applications include market segmentation, customer profiling, fraud detection, evaluation of retail promotions, and credit risk analysis. Law enforcement agencies deal with mass data to investigate the crime and its amount is increasing due to the development of processing the data by using computer. Now new challenge to discover knowledge in that data is confronted to us. It can be applied in criminal investigation to find offenders by analysis of complex and relational data structures and free texts using their criminal records or statement texts. This study was aimed to evaluate possibile application of data mining and its limitation in practical criminal investigation. Clustering of the criminal cases will be possible in habitual crimes such as fraud and burglary when using data mining to identify the crime pattern. Neural network modelling, one of tools in data mining, can be applied to differentiating suspect's photograph or handwriting with that of convict or criminal profiling. A case study of in practical insurance fraud showed that data mining was useful in organized crimes such as gang, terrorism and money laundering. But the products of data mining in criminal investigation should be cautious for evaluating because data mining just offer a clue instead of conclusion. The legal regulation is needed to control the abuse of law enforcement agencies and to protect personal privacy or human rights.

• Korean Journal of Ecology and Environment
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• v.53 no.1
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• pp.31-45
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• 2020

The biological indices based on the community structure with species richness and/or abundance are commonly used to assess aquatic ecosystem health. Meanwhile, recently functional traits-based approach is considered in ecosystem health assessment to reflect ecosystem functioning. In this study, we developed a database of biological traits for 136 taxa consisting of major stream insects (Ephemeroptera, Plecoptera, Trichoptera, Coleoptera, and Odonata) collected at Korean streams on the nationwide scale. In addition, we obtained environmental variables in five categories (geography, climate, land use, hydrology and physicochemistry) measured at each sampling site. We evaluated the relationships between community indices based on taxonomic diversity and functional diversity estimated from biological traits. We classified sampling sites based on similarities of their environmental variables and evaluated relations between clusters of sampling sites and diversity indices and biological traits. Our results showed that functional diversity was highly correlated with Shannon diversity index and species richness. The six clusters of sampling sites defined by a hierarchical cluster analysis reflected differences of their environmental variables. Samples in cluster 1 were mostly from high altitude areas, whereas samples in cluster 6 were from lowland areas. Non-metric multidimensional scaling (NMDS) displayed similar patterns with cluster analysis and presented variation of taxonomic diversity and functional diversity. Based on NMDS and community-weighted mean trait value matrix, species in clusters 1-3 displayed the resistance strategy in the life history strategy to the environmental variables whereas species in clusters 4-6 presented the resilience strategy. These results suggest that functional diversity can complement the biological monitoring assessment based on taxonomic diversity and can be used as biological monitoring assessment tool reflecting changes of ecosystem functioning responding to environmental changes.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.18 no.4
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• pp.29-41
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• 2015

Abandoned paddy field provides an excellent opportunity to improve the species diversity and habitat quality. Ecological characteristic on the changing of plant communities at different seral stages is a major basis data for ecological restoration. In this study, we investigated changes of the species composition and community indices on the plant community associated with abandonment of cultivated rice paddies. The ecological stability of the habitat was evaluated by using eco-floristic characters(Di; Disturbance index, AUI; Actual urbanization index). Survey sites were grouped into six stages(stageI (${\leq}3years$), stageII(3-5years), stageIII(5-7years), stageIV(7-10years), stageV(10-15years), stageVI(${\geq}20years$). Vegetation investigation was done from May 2009 to October 2012 and carried out phytosociological approach. The total flora were summarized as 176 taxa including 58 families, 127 genera, 157 species, 3 subspecies, 15 varieties and 1 forms. At each of successional stages, 64 taxa in stage I, 34 taxa in stage II, 84 taxa in stage III, 83 taxa in stage IV, 92 taxa in stage V, 23 taxa in stage VI were identified. Of the occurrence plants, the species with the highest r-NCD value were Alopecurus aequalis, Juncus effuusus var. decipiens, Persicaria thunbergii, Artemisia princeps, Salix koreensis and Alnus japonica at each stages. Herbaceous annual plants were dominated in the early stage, but its r-NCD value declined in the middle stage and the late stage. On the other hand, herbaceous perennial plants and Persicaria thunbergii, annual hydrophytes, increases in the middle stage. Woody plant and herbaceous plant which appeared in the forest edge increases in the late stage. Community indices correlate with successional stages. Richness and diversity index increase along the successional gradient. But dominance index decrease along the successional gradient. Evenness index was correlated with lower. In the ecological stability analysis of the habitat that evaluated by eco-floristic characters, stage I was the most unstable habitat. And the stability of the habitat has improved according to the successional stage.

• Korean journal of applied entomology
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• v.53 no.3
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• pp.247-260
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• 2014

To identify the species of Trichogramma occurring in the corn fields of Korea as egg parasitoids of Ostrinia furnacalis, we sequenced the full-length of ITS2 nuclear rDNA from 112 parasitoids collected during this study. As a reference to distinguish species, we also retrieved full-length ITS2 sequences of 60 Trichogramma species from the NCBI GenBank database. On the basis of the size and 3'terminal sequence pattern of the ITS2 sequences, the Trichogramma samples collected in this study were divided into three groups (K-1, -2, and -3). Evolutionary distances (d) within and between groups based on ITS2 sequences were estimated to be ${\leq}0.005$ and ${\geq}0.080$, respectively. In the net average distance between groups or species, the d value between K-1 and T. ostriniae, K-2 and T. dendrolimi, and K-3 and T. confusum was the lowest, with values of 0.016, 0.001, and 0.002, respectively. In the phylogenetic tree, K-1 and K-2 were clustered with T. ostriniae and T. dendrolimi, respectively. However, K-3 was clustered with three different species, namely, T. confusum, T. chilonis, and T. bilingensis. NCBI BLAST results revealed that parasitoids belonging to K-1 and K-2 showed 99% identity with T. ostriniae and T. dendrolimi, respectively. Parasitoids in K-3 collected from Hongcheon showed 99-100% identity with T. confusum and T. chilonis, and one parasitoid in K-3 collected from Gochang had 98% identity with T. bilingensis, T. confusum, and T. chilonis. On the basis of these results, we infer that the species of Trichogramma collected in this study are closely related to T. ostriniae (K-1) and T. dendrolimi (K-2). However, it was not possible to distinguish species of K-3 using the ITS2 sequence alone.

• Publications of The Korean Astronomical Society
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• v.36 no.3
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• pp.47-63
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• 2021

Variability is one of the major characteristics of Active Galactic Nuclei (AGN), and it is used for understanding the energy generation mechanism in the center of AGN and/or related physical phenomena. It it known that there exists a time lag between AGN light curves simultaneously observed at different wavelengths, which can be used as a tool to estimate the size of the area that produce the radiation. In this paper, We present long term near-infrared variability of optically bright type 1 AGN using the Wide-field Infrared Survey Explorer data. From the Milliquas catalogue v6.4, 73 type 1 QSOs/AGN and 140 quasar candidates are selected that are brighter than 18 mag in optical and located within 5 degree around the ecliptic poles. Light curves in the W1 band (3.4 ㎛) and W2 band (4.6 ㎛) during the period of 2010-2019 were constructed for these objects by extracting multi-epoch photometry data from WISE and NEOWISE all sky survey database. Variability was analyzed based on the excess variance and the probability P_var. Applying both criteria, the numbers of variable objects are 19 (i.e., 26%) for confirmed AGN and 12 (i.e., 9%) for AGN candidates. The characteristic time scale of the variability (τ) and the variability amplitude (σ) were derived by fitting the DRW model to W1 and W2 light curves. No significant correlation is found between the W1/W2 magnitude and the derived variability parameters. Based on the subsample that are identified in the X-ray source catalog, there exists little correlation between the X-ray luminosity and the variability parameters. We also found four AGN with changing W1-W2 color.